Method and system for spread spectrum code acquisition

ABSTRACT

A code acquisition module for a direct sequence spread spectrum (DSSS) receiver includes: a Sparse Discrete Fourier transform (SDFT) module configured to perform an SDFT on a finite number of non-uniformly distributed frequencies comprising a preamble of a received DSSS frame to calculate Fourier coefficients for the finite number of non-uniformly distributed frequencies; a multiplier configured to multiply the Fourier coefficients for the finite number of non-uniformly distributed frequencies of the received DSSS frame by complex conjugate Fourier coefficients for the finite number of non-uniformly distributed frequencies to generate a cross-correlation of the received DSSS frame and the complex conjugate Fourier coefficients; and a filter module configured to input the cross-correlation and output a delay estimation for the received DSSS frame.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application No.62/593,803, filed Dec. 1, 2017, the contents of which are herebyincorporated by reference in their entirety for all purposes.

BACKGROUND OF THE INVENTION

Techniques for spread spectrum code acquisition have been developed,including systems for direct sequence systems. Despite the progress madein spread spectrum code acquisition techniques, there is a need in theart for improved methods and systems related to spread spectrum codeacquisition.

SUMMARY OF THE INVENTION

Apparatuses and methods for spread spectrum communication systems andcoarse code acquisition in a direct sequence spread spectrum (DSSS)receiver are provided.

According to various aspects there is provided a method forsynchronizing a direct sequence spread spectrum (DSSS) frame. In someaspects, the method may include: generating a preamble-codeword in afrequency domain for the DSSS frame by selecting a finite number ofnon-uniformly distributed frequencies corresponding to frequenciesdetectable by a Sparse Discrete Fourier Transform (SDFT) at whichspectral peaks will occur; generating a preamble in a time domain basedon the preamble-codeword; prepending the preamble to a coded data streamto form the DSSS frame; and transmitting the DSSS frame.

Each of the finite number of non-uniformly distributed frequencies mayhave higher spectral power than a background power spectral density ofthe preamble-codeword. The finite number of non-uniformly distributedfrequencies may be randomly selected frequencies or specificallyselected frequencies. A different preamble-codeword may be generatedafter the preamble-codeword has been used for a predetermined period oftime.

The method may further include: receiving the DSSS frame; generatingsparse Fourier coefficients of the preamble-codeword by performing theSDFT on the preamble; generating complex conjugates of the sparseFourier coefficients based on a reference codeword; and multiplying thesparse Fourier coefficients by the complex conjugates of the sparseFourier coefficients. The reference codeword may be thepreamble-codeword agreed upon in advance between a transmitter and areceiver.

The method may further include generating a delay estimation signal byapplying an iterative filtering algorithm to results of themultiplication. The method may further include generating a delayestimation signal by applying a Sparse inverse Discrete FourierTransform (SiDFT) algorithm to results of the multiplication.

According to various aspects there is provided a code acquisition modulefor a direct sequence spread spectrum (DSSS) receiver. In some aspects,the code acquisition module may include: a Sparse Discrete Fouriertransform (SDFT) module configured to perform an SDFT on a finite numberof non-uniformly distributed frequencies included in a preamble of areceived DSSS frame to calculate Fourier coefficients for the finitenumber of non-uniformly distributed frequencies; a multiplier configuredto multiply the Fourier coefficients for the finite number ofnon-uniformly distributed frequencies of the received DSSS frame bycomplex conjugate Fourier coefficients for the finite number ofnon-uniformly distributed frequencies to generate a cross-correlation ofthe received DSSS frame and the complex conjugate Fourier coefficients;and a filter module configured to input the cross-correlation and outputa delay estimation for the received DSSS frame.

The finite number of non-uniformly distributed frequencies may includesparsely allocated spectral peaks determined by a preamble-codeword. Thecomplex conjugate Fourier coefficients may be calculated based on areference codeword. The reference codeword may be a preamble-codewordagreed upon in advance by the DSSS receiver and a transmitter.

The filter module may be configured to accept an input signal from themultiplier, apply an iterative filtering algorithm or a Sparse inverseDiscrete Fourier Transform (SiDFT) algorithm to the input signal, andoutput a delay estimation signal. The SDFT module, the multiplier, andthe filter module may be implemented by a digital signal processor.

According to various aspects there is provided an optical/electricalcode acquisition module for a direct sequence spread spectrum (DSSS)receiver. In some aspects, the optical/electrical code acquisitionmodule may include: a first optical frequency comb configured togenerate a plurality of first comb frequencies at a first frequencypitch; a second optical frequency comb configured to generate aplurality of second comb frequencies at a second frequency pitchdifferent than the first frequency pitch; an optical modulatorconfigured to modulate the first comb frequencies with a received DSSSsignal including a preamble to generate a modulated signal havingspectral copies of the DSSS signal on different optical wavelengths ofthe first comb frequencies, wherein the preamble includes apreamble-codeword for the DSSS signal including a selected plurality ofnon-uniformly distributed frequencies at which spectral peaks will occurwithin a communication bandwidth; an optical module configured tocombine the modulated signal from the optical modulator and the secondcomb frequencies to generate a plurality of optical output signals; awavelength demultiplexer configured to demultiplex the plurality ofoptical output signals; and a plurality of balanced detectors configuredto detect only the selected plurality of non-uniformly distributedfrequencies comprising the preamble-codeword at which the spectral peakswill occur. Each of the plurality of balanced detectors is configured togenerate output signals corresponding to a detected frequency.

The optical/electrical code acquisition module may further include: aprogrammable device, for example, but not limited to, a digital signalprocessor, configured to accept the output signals from the plurality ofbalanced detectors, generate complex conjugates of the preamble-codewordbased on a reference codeword, multiply the DSSS signal by the complexconjugates of the preamble-codeword, apply a filtering algorithm to theoutput signals, and output a delay estimation signal. The referencecodeword may be the preamble-codeword agreed upon in advance between atransmitter and the DSSS receiver.

The selected plurality of non-uniformly distributed frequencies definedby the preamble-codeword may correspond to frequencies of a SparseDiscrete Fourier transform (SDFT). The plurality of balanced detectorsmay be configured to output signals corresponding to Fouriercoefficients of the SDFT.

Numerous benefits are achieved by way of the various embodiments overconventional techniques. For example, the various embodiments providemethods and systems that can be used to overcome the limitations ofconventional electronic communications systems to implement highcoding-gain direct sequence spread spectrum (DSSS) systems. In someembodiments, a synthesized preamble sequence in conjunction with aSparse Discrete Fourier Transform (SDFT) engine may enable high codinggain. In other embodiments, an optical/electrical solution using twosets of optical frequency combs may be implemented. These and otherembodiments along with many of its advantages and features are describedin more detail in conjunction with the text below and attached figures.

BRIEF DESCRIPTION OF THE DRAWINGS

The various embodiments now will be described more fully hereinafterwith reference to the accompanying drawings, which are intended to beread in conjunction with both this summary, the detailed description andany preferred and/or particular embodiments specifically discussed orotherwise disclosed. This invention may, however, be embodied in manydifferent forms and should not be construed as limited to theembodiments as set forth herein; rather, these embodiments are providedby way of illustration only and so that this disclosure will bethorough, complete and will fully convey the full scope of theembodiments to those skilled in the art.

FIG. 1A illustrates an example of a spectrally synthesizedpreamble-codeword in the frequency domain in accordance with variousaspects of the present disclosure;

FIGS. 1B and 1C illustrate an example of real and imaginary parts,respectively, of an example single quadrature preamble in the timedomain generated from the spectrally synthesized preamble-codeword ofFIG. 1A;

FIG. 2A illustrates an example of a spectrally synthesizedpreamble-codeword having peak power spectral points randomly distributedwithin negative and positive frequencies in the frequency domain;

FIGS. 2B and 2C illustrate examples of a real part and an imaginarypart, respectively, of an example double quadrature preamble in the timedomain generated from the spectrally synthesized preamble-codeword ofFIG. 2A in accordance with various aspects of the present disclosure;

FIG. 3 illustrates an example of a transmitted DSSS frame formed byprepending a time domain preamble to a pseudorandom binary sequence(PRBS) coded payload in accordance with various aspects of the presentdisclosure;

FIGS. 4A-4D illustrate examples of power spectral densities of atransmitted frame for different preamble to payload ratios in accordancewith various aspects of the present disclosure;

FIG. 5 is a block diagram illustrating a DSSS receiver in accordancewith various aspects of the present disclosure;

FIG. 6 is a block diagram of an iterative filtering algorithm used fordelay estimation in accordance with various aspects of the presentdisclosure;

FIG. 7 is a block diagram of a hybrid optical/electrical implementationfor a code acquisition block in accordance with various aspects of thepresent disclosure;

FIG. 8 is a plot illustrating performance of the presently disclosedcode acquisition technique compared to conventional techniques;

FIG. 9 is a flowchart of a method for generating a synthesizedpreamble-codeword for a DSSS signal in accordance with various aspectsof the present disclosure; and

FIG. 10 is a flowchart of a method for decoding a DSSS signal with asynthesized preamble-codeword in accordance with various aspects of thepresent disclosure.

DETAILED DESCRIPTION OF SPECIFIC EMBODIMENTS

Embodiments in accordance with the present disclosure relate generallyto spread spectrum communication systems and in particular to coarsecode acquisition in a direct sequence spread spectrum (DSSS) receiverdemodulation block. The method may be of interest for wirelessultra-wide-band (UWB) and secure communication links requiring a largespreading factor and fast transmitter and receiver synchronization.

The spread spectrum technique was originally motivated by securedwireless radio communication links in the post-World War II era. Thebasic idea was to use a unique key to spread the modulated signalbandwidth in the frequency domain to bring the power spectral density(PSD) of the transmitted signal below the receiver noise floor and makeit nearly impossible to differentiate the signal from the thermal noise.That is to say, undesired receivers/listeners who did not have access tothe spreading key could not even notice if there was a transmittedwireless signal. On the other hand, a desired receiver could use thesame key to despread the coded signal out of the noise and thereforemake the original signal detectable. In this way, a secured transmissionlink with low probability of intercept (LPI) could be establishedbetween the parties who have the key.

Another advantage of spread spectrum systems is their resiliency tocommunication jamming techniques. While the despreading operation at thereceiver elevates the power spectral density of the desired signal awayfrom noise floor, at the same time it spreads any undesired signals,including jamming signals, and decreases their PSD until it approachesnoise floor.

Different methods were originally proposed for spread spectrummodulation including chirp spread spectrum (CSS), direct sequence spreadspectrum (DSSS), frequency hopping spread spectrum (FHSS), and timehopping spread spectrum (THSS). Among these, the DSSS systems, which areconsidered as one of the most successful spread spectrum systems due toinherent LPI and jamming resilience, are the subject of this disclosure.In DSSS, each data-modulated symbol is multiplied in the time domain bya data-codeword consisting of the multiple, fast 180-degree phasetransitions within a single symbol duration. The shortest phasetransition time in a given data-codeword is called a chip duration, andthe ratio of the symbol duration to the chip duration defines thespreading factor or coding gain. In approximate terms, this is also thedegree of spectral spreading, or equivalently, the degree to whichoriginal data PSD is attenuated.

A phase transition pattern, commonly referred to as the data-codeword,is generated in a pseudo-noise (PN) manner that has deterministicbehavior with maximal spectral flatness. This class of data-codeword iscalled a pseudo-noise (PN) sequence or maximal length sequence and maybe practically generated in a linear feedback shift registers (LFSR)device. The receiver uses the same data-codeword in order to multiplythe received (i.e., spread) data stream and decode (i.e., despread) thetransmitted data. However, the decoding is successful if and only if thereceived signal and the local de-spreading code generator are preciselysynchronized in time. In the synchronized state, the local codegenerator applies an additional 180-degree phase rotation to thepositions in a symbol that have already experienced the phase shift inthe transmitter. As a result, the coded phase shift pattern is removedfrom the symbols in the receiver and actual bits of data are recovered.

Two phases of synchronization may be used to achieve successfuldecoding: coarse code acquisition, which aligns the incoming codedstream and the local code generator within a time scale that isapproximately equal to the chip duration, and fine tracking, whichbrings the alignment between the received waveform and the data-codewordto within the fraction of the chip, while keeping the alignment fixedvia a feedback scheme commonly referred as delayed locked loop (DLL).

Coarse code acquisition has been recognized as a limitation forimplementation of high coding-gain direct sequence spread spectrum(DSSS) systems. Conventionally, coarse code acquisition is performed byeither a serial search over multiple possible delays or by a fastdigitizer capable of operation at the chip-rate on the receiver side,followed by a digital cross-correlator. The former suffers from slowsynchronization convergence and the latter unnecessarily requiresreplicated hardware devoted to the coarse code alignment. Anotherimpairment of conventional coarse code acquisition relates to theability to synchronize in a low-latency manner.

While conventional synchronization can be accomplished with sufficientcomputational resources that are not limited by dissipation, even inthis case, high coding gain may not be achieved. High-coding gain alsodictates wide spectral spreading that directly defines the chipduration. When spectral spreading exceeds a rate compatible withconventional electronic processors, the synchronization scheme requireseither hardware parallelization or redundancy implied with a subsamplingbackplane. In practical terms, when a spread spectrum receiver requiresspreading in excess of GHz frequencies, the corresponding sub-nanosecondchip duration also requires synchronization electronics to operate at acomparable or faster rate.

While electronic architectures capable of operating at these rates maybe devised, those architectures cannot be realized in adissipation-limited manner, and not in a man-portable device. Even ifthe excessive dissipation involved in ultra-wideband DSSS isdisregarded, a viable synchronization latency problem remains unsolved.

As an illustration, to search for unique synchronization setting over10,000 chips corresponding to 40 dB gain receiver, a solution may befound after approximately 100,000,000 trials. This means that physicallatency imposed on a DSSS link would be measured in terms ofapproximately 10,000 data bits—an unacceptable performance in anycommunication link. Further, if the transmitter and receiver are notstationary, as is the case in both commercial applications and defenseapplications where mobile platform can move at rate exceeding Machnumber, then the synchronization latency requirement becomes much morestringent. In this case, the maximum synchronization latency is definedby the ratio of the relative transmitter/receiver velocity and the speedof light (i.e., the propagation of radio waves). For a slow orstationary receiver, this number is negligible. However, for an exampleMHz-rate bit stream spread over 10 GHz (i.e., a 100 picosecond chipduration), operating on a subsonic (i.e., 300 m/s speed) platform, thenits synchronization must be performed in approximately less than 10microseconds, or in less than five native bits.

Known synchronization technique do not approach this requirement, whichis one of the primary reasons why ultra-wideband DSSS channels have notbeen adopted to date, in spite of attractive security features that theyinherently offer. As the increase in physical bandwidth is steadilydriven in the commercial sector, a similar consideration is applicablethere, and particularly so for transportation platforms where the userrequires both security and high data rate at minimal latency.

The present embodiments advantageously overcome deficiencies ofconventional communication systems by enabling low latency and lowcomputation cost synchronization apparatus for spread spectrumcommunication systems.

Some embodiments of the present invention relate to methods for receiversynchronization of direct sequence spread spectrum (DSSS) communicationsystems having a large spreading factor (e.g., coding gain greater than40 dB). The synchronization method may involve designing apreamble-codeword designed to not only preserve the security of thecommunication link, but also to reduce the complexity of the DSSSreceiver at the code acquisition stage. The technique for DSSS receiversynchronization is based, in some embodiments, on a sparse Fourieranalysis that calculates the sparse Fourier coefficients of the designedpreamble to achieve cross-correlation in frequency domain. Thecomplexity of the receiver is further reduced by circumventing theinverse Fourier transform and estimating the delay information throughan adaptive iterative filtering algorithm in the sparse Fourier domainin some embodiments.

Aspects of the various embodiments provide a method for coarse codeacquisition that allows for fast and low complexity synchronization ofDSSS signals with large coding gain (e.g., more than 40 dB) receivers.The method may include the following components: a spectrallysynthesized preamble, a Sparse Discrete Fourier Transform (SDFT) module,and specialized iterative filtering.

In some embodiments, the synthesized preamble may be placed at thebeginning of a transmitted coded data frame that has been coded usingthe synthesized preamble. At the receiver, the electrical SDFT isapplied to the incoming data stream. The SDFT precisely targets thespectral positions in the preamble spectral range that are synthesizedto have substantial power. The electrical SDFT is accomplished bytechniques such as, but not limited to, non-uniform time domain samplingor a poly-phase filter banks architecture. In other embodiments, theSDFT is performed in a hybrid optical/electrical domain using two setsof optical frequency combs having different frequency spacing. Thecalculated SDFT coefficients of the incoming data stream are multipliedby the complex conjugate SDFT coefficients of the preamble-codeword toproduce the frequency domain representation of the cross-correlationfunction. In still other embodiments, a Sparse inverse Discrete FourierTransform (SiDFT) may be performed to retrieve the time domaincross-correlation function which contains delay and synchronizationinformation. In yet other embodiments, the delay information may beextracted directly from the frequency domain cross-correlation functionusing adaptive and iterative filtering.

The method described herein is unique when compared with other knownprocesses and solutions in that it: (1) can synchronize a spreadspectrum communication link substantially faster than conventionaltechniques; (2) can achieve a synchronization state on high-accelerationand platforms moving at substantial speed (3) can achieve thesynchronization with a low signal to noise ratio (SNR) regime; (4) canachieve the synchronization in contested electromagnetic environmentsreplete with artificial jamming and/or heavy clutter backgrounds; (5)can operate in the presence of a multi-path interference (MPI) map forthe physical configuration of the specific link; and (6) allows forsignificant reduction in complexity, receiver power consumption, andcomputational expenses.

More specifically, the various embodiments may: (1) exploit aspecifically synthesized preamble-codeword; (2) allow for sparsecalculation and operation for time and frequency domain conversions; and(3) enable the use of adaptive filtering for delay estimation. Amongother things, embodiments may provide a synchronization technique forspread spectrum system with large spreading factor (i.e., more than 40dB) that does not suffer from any of the problems or deficienciesassociated with prior solutions. The various embodiments may simplifyconstruction of synchronization scheme and reduce power consumption andcomplexity associated with transmitter/receiver synchronization.

In accordance with aspects of the present disclosure, embodiments mayinclude two major sections: (1) a spectrally-sparse preamble design ruleto synthesize the preamble-codeword; and (2) a receiver architecturedesign which uses the specific preamble-codeword to synchronize andaccurately decode the incoming data stream. Herein, the term“preamble-codeword” will be used to denote the synthesized pattern whichhas spectrally sparse frequencies and is placed at the header of thedata packet, and term “data-codeword” will be used for pseudo-noisebinary phase transition pattern used to encode the payload of thepacket.

FIG. 1A illustrates an example of a spectrally synthesizedpreamble-codeword 110 in the frequency domain in accordance with variousaspects of the present disclosure. FIGS. 1B and 1C illustrate an exampleof a real part 115 and an imaginary part 120, respectively, of anexample single quadrature preamble in the time domain generated from thespectrally synthesized preamble-codeword of FIG. 1A. As illustrated inFIG. 1A, it should be noted that the spectrally synthesizedpreamble-codeword 110 is symmetric about zero frequency, therefore thetime domain signal (i.e., the preamble) will have no imaginarycomponent.

The preamble-codeword design may begin with spectral shaping byselecting non-uniformly distributed spectral locations 112 within thecommunication bandwidth. The number of frequencies selected may bedetermined based on the sparse density processing capability of the DSSSreceiver. In accordance with various aspects of the present disclosure,the frequencies may be randomly selected or specific frequencies may beselected. Referring to FIG. 1A, preamble-codeword spectral shaping,i.e., the selection of the frequencies at which spectral peaks occur,may correlate with a plurality of frequencies (i.e., spectral locations112) for which coefficients may be determined when the SDFT is performedat the receiver. The SDFT calculates the Fourier components equal to thenumber of frequencies in the preamble-codeword.

These points on the spectrum (i.e., spectral peaks) may have higherspectral power compared to the background power spectral density (PSD)114 of the preamble-codeword. The contrast between the peak powerspectral points and background PSD may be another parameter for preamblespectral/time visibility. In FIG. 1A, the contrast is approximately 7dB, but this is not required by the present embodiments and any otherarbitrary contrast values can be achieved.

In the embodiment illustrated in FIG. 1A, the peak power spectral points112 for the synthesized the preamble-codeword 110 may be chosensymmetrically around a center frequency (i.e., zero frequency forbaseband preamble design). In this case, the time domain preambleremains in real quadrature as illustrated in FIGS. 1B and 1C (i.e., noimaginary component as shown in FIG. 1C). In some embodiments, peakpower spectral points for the preamble-codeword in the frequency domainmay be distributed randomly within negative and positive frequencies,which makes the preamble complex (i.e., contains both real and imaginaryquadrature) in the time domain.

FIG. 2A illustrates an example of a spectrally synthesizedpreamble-codeword 210 having peak power spectral points 212 randomlydistributed within negative and positive frequencies in the frequencydomain in accordance with various aspects of the present disclosure.FIGS. 2B and 2C illustrate examples of a real part 215 and an imaginarypart 220, respectively, of an example double quadrature preamble in thetime domain generated from the spectrally synthesized codeword of FIG.2A in accordance with various aspects of the present disclosure.

As illustrated in FIGS. 2A-2C, when the peak power spectral points 212are distributed randomly within negative and positive frequencies in thefrequency domain, the preamble contains real 215 and imaginary 220components in the time domain. In this implementation, anin-phase/quadrature (I/Q) modulator may be required for up-convertingthe preamble into the desired transmission band using techniques knownto those of skill in the art to upconvert two quadrature signals usingsine and cosine for real and imaginary parts and adding them, comparedto using only cosine for single quadrature upconversion.

The preamble-codeword may be agreed upon between the transmitter andreceiver in advance. An SDFT module at the receiver specificallyconsiders the power spectral peaks of the preamble, which contain nearlyall the preamble energy, as the sparse points for the Fourier transformcalculation. Therefore, the need for full rate Fourier analysis at thereceiver becomes unnecessary and the complexity of the receiver may bereduced by several orders of magnitude by computation of the sparsecoefficients due to the fact that calculating the Fourier coefficientscan be limited to only a subset of all coefficients that is defined bythe sparse spectral peaks locations. For example, if the subset includes10 spectral peak locations out of 100 total spectral samples, the SDFTcalculates only a 10 point DFT compared to a 100 point DFT that would becalculated for a full Fourier analysis of the 100 spectral samples.

After the preamble-codeword spectral shaping has been performed, a timedomain signal (i.e., the preamble) corresponding to the synthesizedpreamble-codeword may be generated, for example using adigital-to-analog converter (DAC) or by another method. For example, thetime domain signal 115, 120 in FIGS. 1B and 1C may be generated based onthe synthesized preamble-codeword 110 in FIG. 1A. Since the synthesizedpreamble-codeword 110 is symmetric about zero frequency, the time domainpreamble will have no imaginary component. Similarly, the time domainsignal 215, 220 in FIGS. 2B and 2C may be generated based on thesynthesized preamble-codeword 210 in FIG. 2A. In FIG. 2A the synthesizedpreamble-codeword 210 is not symmetric about zero frequency; thus, thetime domain preamble contains real components 215 and imaginary 220components.

The preamble may be generated by inputting the synthesizedpreamble-codeword into a digital-to-analog converter (DAC) andperforming an inverse Fourier transform or iDFT. The DAC may have aminimum required signal-to-noise and distortion ratio (SINAD) greaterthan the spectral contrast of the synthesized preamble-codeword (e.g.,the synthesized preamble-codeword 110 or the synthesizedpreamble-codeword 210).

FIG. 3 illustrates an example of a transmitted DSSS frame 300 formed byprepending a time domain preamble 310 generated from a synthesizedpreamble-codeword to a pseudo-random binary sequence (PRBS) coded datastream (i.e., payload) 320 in accordance with various aspects of thepresent disclosure. While the PRBS coded data stream is represented inFIG. 3 as a signal having a constant amplitude, this is only for ease ofrepresentation to differentiate the time domain preamble from the PRBScoded data stream. One or ordinary skill in the art will appreciate thatthe PRBS coded data stream is a time varying signal. The preamble 310may be included in each transmitted DSSS frame 300. Each data-modulatedsymbol in the payload may be multiplied in the time domain by themultiple, fast 180-degree phase transitions within a single symbolduration defined by the data-codeword. The coded data payload 320 of theframe 300 may use pseudo-random binary sequences (PRBS) for spreadingthat are suited for a conventional fine tracking algorithm. The finetracking algorithm may use known delay lock loop (DLL) techniques.

In accordance with various aspects of the present disclosure, a newpreamble-codeword be may periodically or randomly synthesized/hopped tominimize the possibility of unintended detection/decoding of transmittedinformation. For example, a different preamble, with different spectralpeak locations, may be synthesized after a it has been used for apredetermined period of time. Alternatively, a different preamble may besynthesized after a codeword has been used for a predetermined number oftransmitted frames. As a further alternative, a different preamble maybe synthesized after a it has been used for a random period of time or arandom number of transmitted frames. One of ordinary skill in the artwill appreciate that other schemes for determining to synthesize a newcode word may be used without departing from the scope of the presentdisclosure.

FIGS. 4A-4D illustrate examples of power spectral densities oftransmitted DSSS frames for different preamble to payload ratios inaccordance with various aspects of the present disclosure. FIG. 4Aillustrates a power spectral density estimate for a DSSS frame having nopreamble 410. The power spectral density estimate FIG. 4A shows a noisefloor 412 of approximately −90 dB/Hz. FIG. 4B illustrates a powerspectral density estimate for a DSSS frame having a preamble occupying1% of the frame 420. As can be seen in FIG. 4B, with the preambleoccupying 1% of the frame the noise floor 422 remains approximately −90dB/Hz. Similarly, FIGS. 4C and 4D show that the noise floors 432, 442remains approximately −90 dB/Hz for DSSS frames having preamblesoccupying 5% of the frame 430, and 10% of the frame 440, respectively.The ratio of the preamble duration to payload in each frame may beassigned to properly hide the spectral peaks of the preamble portion inthe white noise spectrum of the payload while the code acquisitionperformance remains intact. Thus, the DSSS frame containing thetransmitted information is also indistinguishable from noise.

FIG. 5 is a block diagram illustrating a DSSS receiver 500 in accordancewith various aspects of the present disclosure. Referring to FIG. 5, theDSSS receiver 500 may include a fast code acquisition module 520, adelay locked loop (DLL)/fine tracking module 530, and adespreading/decoding module 540.

At the DSSS receiver 500, the incoming DSSS modulated signal 510 maysplit into four paths: the first path 512 may be input to the fast codeacquisition module 520; the second path 514 and third path 516 may beinput to the DLL/fine tracking module 530; and the fourth path 518 maybe input to the despreading/decoding module 540. Successful operation ofDLL/fine tracking module 530 and the despreading module 540 may be basedon the performance of the fast code acquisition module 520. In someembodiments, the code acquisition is accomplished rapidly by the fastcode acquisition module 520 to reduce or minimize loss of transmitteddata blocks and may be accurate to within less than or equal to two chipdurations for operation of the fine tracking algorithms.

The fast code acquisition module 520 may include a Sparse DiscreteFourier Transform (SDFT) module 522, a multiplier 524, and an iterativefilter module 526. The code acquisition may begin with the SDFT module522. In some embodiments, the electrical SDFT is accomplished bytechniques such as, but not limited to, non-uniform time domain samplingor a poly-phase filter banks architecture. In some embodiments, the SDFTmay be implemented digitally, for example with an application specificintegrated circuit (ASIC) or other programmable logic device configuredto perform the SDFT. The SDFT module 522 may enable both calculationcomplexity and input/output (I/O) throughput to be scaled by thesparsity ratio of the SDFT (i.e., the ratio of the number of points usedfor the SDFT analysis to the number of points required for a full DFTanalysis).

The SDFT module 522 calculates the Fourier coefficients of thesynthesized preamble-codeword from the preamble received with the DSSSframes based on the sparsely allocated spectral peaks determined by thesynthesized preamble-codeword in the frequency domain. When the receiverreceives the signal, it applies the SDFT to the incoming stream. Thepreamble-codeword is shared between receiver and transmitter. Thetransmitter generates the preamble-codeword and puts it in front of(i.e., prepends it to) the data frame. Thus, the receiver is also awareof the preamble-codeword (i.e., reference codeword) having agreed uponit in advance with the transmitter. The receiver multiplies the incomingSDFT by the conjugate of the reference codeword. The output is sent tothe iterative filter and a relative delay between the received signaland reference codeword is calculated by the iterative filter. TheDiscrete Fourier Transform (DFT) of the preamble-codeword c[n] may becalculated as:

${C\lbrack K\rbrack} = {\sum\limits_{n = 1}^{N}{{c\lbrack n\rbrack}e^{\frac{{- j}\; 2\pi \; {nK}}{N}}}}$

where K∈{full spectrum indices}.

The Sparse Discrete Fourier Transform of the preamble-codeword c[n](i.e., the output 523 of the SDFT module 522) may be calculated as:

${C\lbrack K\rbrack} = {\sum\limits_{n = 1}^{N}{{c\lbrack n\rbrack}e^{\frac{{- j}\; 2\pi \; {nK}}{N}}}}$

where K∈{sparse indices}.

Knowing the synthesized preamble-codeword (i.e., having received thepreamble with the DSSS frame), and adjusting the K∈{sparse indices}based on the sparse set of spectral points agreed upon in advancebetween the transmitter and the receiver, the SDFT module 522 in theDSSS receiver 500 may configure itself to the calculate the Fouriercoefficients of the coded data stream at only the peak power spectralpoints (e.g., the peak power spectral points 122 in FIG. 1) determinedby the synthesized preamble-codeword. Thus, Fourier analysis of the DSSSsignal may be simplified by performing the SDFT to generate only theFourier coefficients for the frequencies corresponding to the spectrallocations determined by the synthesized preamble-codeword.

Once the SDFT coefficients of the synthesized codeword are obtained, thecomplex conjugate SDFT coefficients of the preamble-codeword may begenerated at the DSSS receiver based on the reference codeword.

The SDFT module 522 may calculate the SDFT coefficients 523 of thereceived stream (e.g., the preamble and the PRBS coded data stream 320)and the SDFT coefficients 523 of the incoming stream may be multipliedat the multiplier 524 by the complex conjugate SDFT coefficients C*[K]525 of the synthesized preamble-codeword to generate the Fouriertransform of the cross-correlation 527 between the received incomingstream and the reference preamble-codeword generated at the receiver.The output of the multiplier (i.e., the cross-correlation) may be sentto the iterative filter to calculate the relative delay between thereceived signal and reference codeword.

The cross-correlation (i.e., the output of multiplier) in the frequencydomain contains a linear phase rotation across the coefficients.Equivalently, the cross-correlation function in the time domain carriesa temporal peak that indicates the relative delay between the receivedDSSS signal and the reference preamble-codeword.

In some embodiments, the cross-correlation signal output of themultiplier 524 may be input to an iterative filter block 526. The linearphase rotation across the SDFT coefficient product terms may beextracted directly without further domain conversion by the iterativefilter block 526 using an iterative filtering algorithm. The iterativefilter block 526 may apply the iterative filtering algorithm to thecross-correlation signal and a delay estimation 528 may be generated. Insome embodiments, a Sparse inverse Discrete Fourier Transform (SiDFT)algorithm may be used to estimate the delay. The SiDFT operation on thecross-correlation product coefficients may convert the linear phaserotation into a spike that may appear as a sharp spike. The location ofthe spike with respect to the sequence length may determines the amountof delay.

However, implementation of an iterative filtering algorithm may furthersimplify the delay estimation when compared to the SiDFT algorithm.Thus, the fast code acquisition module 520 may align the incoming codedstream and the local code generator (i.e., the complex conjugatepreamble-codeword generated at the DSSS receiver) within a time scalethat is approximately equal to the chip duration.

The delay estimation 528 output of the iterative filtering module 562may be input to the despreading module 540 for demodulating/decoding ofthe incoming DSSS signal. The despreading module 540 may generate acoded signal advanced by one-half of a chip duration (i.e., an “early”coded signal) and a coded signal delayed by one-half of a chip duration(i.e., a “late” coded signal). The early and late coded signals may beinput to the DLL/fine tracking module 530. The output of the DLL/finetracking module 530 may be input to the despreading module 540 tosynchronize decoding of the DSSS signal. The DLL/fine tracking module530 may output the clock signal that is corrected by the calculatederror signal. The clock signal may seed the code generator module indespreading block 540 to compensate the residual fine delay (i.e.,within one chip duration) and keep the incoming stream and localdata-codeword generator in a synchronized state.

FIG. 6 is a block diagram of an iterative filtering algorithm 600implemented in an iterative filtering module 526 for estimating delay inaccordance with various aspects of the present disclosure. Referring toFIG. 6, the iterative filtering algorithm 600 may include an infiniteimpulse response (IIR) filter 610 in a feedforward direction with asingle pole at e^(jπâ) where â is the estimated phase slope (orequivalently the time delay) of the input complex coefficients. Anyvalue of â maps into a delay value between the incomingpreamble-codeword and the reference preamble-codeword generated at thereceiver side. A first iteration may begin with an initial guess for â₀.

An error signal 620 may be generated based on filtering of the inputcomplex coefficients with the IIR filter having a single pole at e^(jπâ)⁰ . The new estimation for the pole position, â₁, may be derived fromthe error signal. This iteration may continue until the differencebetween the two consecutive estimated poles, â_(k+1) and â_(k), becomessmaller than an equivalent of single chip delay. The output of theiterative filtering module 562 may be input to the despreading module540 as a coarse delay estimation. One of ordinary skill in the art willappreciate that other iterative filtering algorithms may be implementedwithout departing from the scope of the present disclosure.

While the described embodiment employs an iterative filtering algorithm,embodiments of the present disclosure are not limited to thisimplementation. In some embodiments, the product of the SDFTcoefficients and complex conjugate of the Fourier coefficients of thepreamble may be passed to a Sparse inverse DFT (SiDFT) engine to extractthe temporal peak and relative delay.

In some embodiments, the SDFT may be performed in a hybrid computationfree optical/electrical architecture. FIG. 7 is a block diagram of ahybrid optical/electrical implementation for a code acquisition module700 in accordance with various aspects of the present disclosure. Thehybrid optical/electrical code acquisition module 700 may include afirst optical frequency comb 710, a second optical frequency comb 720,an optical modulator 730, a hybrid optical module 740, an opticalwavelength demultiplexer 750, a plurality of detectors 760, and a filter770.

In implementations of the optical/electrical hybrid architecture, afirst set of frequency combs 710 having a first frequency pitch and asecond set of frequency combs 720 having a second frequency pitch may beused to extract SDFT coefficients. The first optical frequency pitch andthe second optical frequency pitch may be different frequency pitches.

The optical modulator 730 may modulate the frequencies generated by thefirst optical frequency comb 710 using the received DSSS signal togenerate spectral copies of the DSSS signal on the tones (i.e.,different optical wavelengths) of the first optical frequency comb 710.The second optical frequency comb 720 may act as a local oscillator. Themodulated optical signal from the first optical frequency comb 710 andthe optical signal (i.e., local oscillator signal) from the secondoptical frequency comb 720 may be combined by the 90° hybrid opticalmodule 740. The 90° hybrid optical module 740 may act as a coherentreceiver and output four signals: a modulated signal plus localoscillator signal 742 a, a modulated signal minus local oscillatorsignal 742 b, a modulated signal plus conjugate of local oscillatorsignal 742 b, and a modulated signal minus conjugate of local oscillatorsignal 742 d. The output signals of the hybrid optical module 740 may beinput to the optical wavelength demultiplexer 750.

The optical wavelength demultiplexer 750 may include a plurality ofdemultiplexer modules. In some implementations, four demultiplexermodules may be used. Each demultiplexer module may be configured todemultiplex one output 742 a-d of the hybrid optical module 740. Thedemultiplexed signals may be detected by the plurality of detectors 760.The plurality of detectors D₁-D_(N) 760 may be coherent detectors. Insome embodiments, each coherent detector may include two balanceddetectors, with each balanced detector having two PIN diodes (i.e., atotal of four PIN diodes for each coherent detector). Each of theplurality of detectors D₁-D_(N) 760 receives a signal from each of theplurality of demultiplexer modules. For example, for implementationsusing four demultiplexer modules, each detector D₁-D_(N) receives asignal from each demultiplexer module, i.e., each detector D₁-D_(N)receives four signals. The plurality of detectors D₁-D_(N) 760 maycorrelate with the plurality of frequencies (i.e., spectral locations122) for which the SDFT coefficients specified by the synthesizedcodeword may be determined. The spectral peak locations are known to thereceiver 500. The receiver 500 may activate the detectors matching thespectral locations. Each of the active detectors D₁-D_(N) 760 maycoherently detect SDFT coefficients. Each of the detectors D₁-D_(N) mayoutput in-phase and quadrature (I & Q) signals representing the detectedSDFT coefficients 765. Thus, the optical/electrical hybrid architecturemay stream the SDFT coefficients in a computation free manner.

The SDFT coefficients 765 may be input to a digital signal processor(DSP) 770 or other programmable device configured to perform themultiplication by the complex conjugate SDFT coefficients of thereference preamble-codeword. The complex conjugate coefficients of thepreamble-codeword may be generated by the DSP 770.

The DSP 770 or other programmable device may further implement aniterative filtering algorithm or a SiDFT algorithm to generate a delayestimation for output to the despreading module 540. For example, theDSP 770 may implement the iterative filtering algorithm 600 as describedwith respect to FIG. 6. The output of the DSP 770 is the output 528 ofthe fast code acquisition module 520 that may be sent to the despreadingmodule 540. The optical front end 700 is one realization of the SDFTmodule 522. In this implementation, the DSP 770 may perform theoperations described with respect to the fast code acquisition module520.

FIG. 8 is a plot 800 illustrating performance of the presently disclosedcode acquisition technique compared to conventional techniques.Referring to FIG. 8, the calculated performance curve for the presentlydisclosed code acquisition technique 810 with a preamble generated froma synthesized preamble-codeword is compared to a conventional technique820 without the preamble and a conventional full-scale receiver 830. Theperformance curve for the conventional technique 830 was calculatedbased on a full scale DFT of 8191 points. The curve for the conventionalSDFT technique without preamble 820 and the curve for the SDFT withpreamble 810 of the present disclosure were both calculated using a SDFThaving 127 points. As can be seen in FIG. 8, the curves show theefficiency of the presently disclosed code acquisition technique 810with nearly the same performance when compared to the conventionalfull-scale receiver 830.

FIG. 9 is a flowchart illustrating a method 900 for generating asynthesized preamble-codeword for a DSSS signal in accordance withvarious aspects of the present disclosure. Referring to FIG. 9, at block910 a preamble-codeword may be synthesized in the frequency domain. Forexample, a plurality of spectral locations within the frequency band ofthe DSSS communication system may be selected, i.e., thepreamble-codeword may be spectrally shaped. The number of frequenciesselected may be determined based on the sparse density processingcapability of the DSSS receiver. The frequencies may be randomlyselected or specific frequencies may be selected. These points on thespectrum (i.e., spectral peaks) may have higher spectral power comparedto the background PSD of the codeword.

The selected frequencies for spectrally shaping the codeword maycorrespond to frequencies for which the SDFT module in the DSSS receiverwill generate Fourier coefficients. The SDFT module at the receiver mayspecifically consider the power spectral peaks of the preamble, whichcontain nearly all the preamble energy, as the sparse points for theFourier transform calculation.

At block 920, a time domain preamble for a coded DSSS frame may besynthesized. A time domain signal corresponding to the synthesizedpreamble-codeword in the frequency domain may be generated, for example,using a DAC or by another method. The DAC may have a minimum requiredsignal-to-noise and distortion ratio (SINAD) greater than the spectralcontrast of the synthesized preamble-codeword (e.g., the synthesizedcodeword 120 or the synthesized codeword 210). One of ordinary skill inthe art will appreciate that other methods of converting the frequencydomain codeword to a time domain preamble may be used without departingfrom the scope of the present disclosure.

At block 930, the preamble may be prepended to a coded data stream. Thedata stream may be coded using pseudo-random binary sequences (PRBS) forspreading. The coded payload of the frame may be generated bymultiplying each data-modulated symbol in the time domain by themultiple, fast 180-degree phase transitions within a single symbolduration defined by the data-codeword. The preamble may be prepended tothe PRBS coded data stream to form a DSSS frame for transmission. Atblock 940, the DSSS frame with the prepended preamble may betransmitted.

In accordance with various aspects of the present disclosure, a newpreamble-codeword may be synthesized to minimize the possibility ofunintended detection/decoding of transmitted information. For example, adifferent preamble-codeword may be synthesized after a preamble-codewordhas been used for a predetermined period of time. Alternatively, adifferent preamble-codeword may be synthesized after a preamble-codewordhas been used for a predetermined number of transmitted frames. As afurther alternative, a different preamble-codeword may be synthesizedafter a preamble-codeword has been used for a random period of time or arandom number of transmitted frames.

It should be appreciated that the specific operations illustrated inFIG. 9 provide a particular method of generating a preamble for a DSSSsignal according to an embodiment. Other sequences of operations mayalso be performed according to alternative embodiments. For example,alternative embodiments may perform the operations outlined above in adifferent order. Moreover, the individual operations illustrated in FIG.9 may include multiple sub-steps that may be performed in varioussequences as appropriate to the individual operation. Furthermore,additional operations may be added or removed depending on theparticular applications. One of ordinary skill in the art wouldrecognize many variations, modifications, and alternatives.

FIG. 10 is a flowchart illustrating a method 1000 for decoding a DSSSsignal with a synthesized preamble-codeword in accordance with variousaspects of the present disclosure. Referring to FIG. 10, at block 1010,a DSSS signal including a preamble may be received. At block 1020, anSDFT may be performed on the DSSS signal to obtain the sparse Fouriercoefficients of the synthesized preamble-codeword in the frequencydomain from the time domain preamble signal.

At block 1030, the complex conjugates of the sparse Fourier coefficientsof the synthesized preamble-codeword may be generated. For example, aDSP module may calculate the complex conjugates of the sparse Fouriercoefficients of the synthesized preamble-codeword that transmitter andreceiver agreed to use in advance. At block 1040, the sparse Fouriercoefficients of the coded data stream of the received DSSS signal may becalculated and multiplied by the complex conjugate of the sparse Fouriercoefficients of the synthesized preamble-codeword. For example, at eachfrequency determined by the SDFT, the multiplier 524 in the fast codeacquisition module 520 may multiply the sparse Fourier coefficients ofthe coded data stream of the DSSS signal calculated by the SDFT module522 by the complex conjugates of the sparse Fourier coefficients of thesynthesized preamble-codeword at that frequency. The multiplication maygenerate the Fourier transform of the cross-correlation between thereceived DSSS signal and the reference complex conjugates of the sparseFourier coefficients of the preamble-codeword.

At block 1050, a delay estimation for the received DSSS signal may begenerated by the fast code acquisition module 520 within a time scalethat is approximately equal to the chip duration. For example, in someembodiments, the cross-correlation signal output of the multiplier 524may be input to an iterative filter block 526. The iterative filterblock 526 may apply an iterative filtering algorithm to thecross-correlation signal to generate a delay estimation. Alternatively,in some embodiments a Sparse inverse Discrete Fourier Transform (SiDFT)algorithm may be used to estimate delay. At block 1060, the delayestimation signal may be input to the despreading module 540 tosynchronize decoding of the DSSS signal.

It should be appreciated that the specific operations illustrated inFIG. 10 provide a particular method of decoding a DSSS signal with apreamble according to an embodiment. Other sequences of operations mayalso be performed according to alternative embodiments. For example,alternative embodiments may perform the operations outlined above in adifferent order. Moreover, the individual operations illustrated in FIG.10 may include multiple sub-steps that may be performed in varioussequences as appropriate to the individual operation. Furthermore,additional operations may be added or removed depending on theparticular applications. One of ordinary skill in the art wouldrecognize many variations, modifications, and alternatives.

The methods 900 and 1000, respectively, may be embodied on anon-transitory computer readable medium, for example, but not limitedto, a memory or other non-transitory computer readable medium known tothose of skill in the art, having stored therein a program includingcomputer executable instructions for making a processor, computer, orother programmable device execute the operations of the methods.

The examples and embodiments described herein are for illustrativepurposes only. Various modifications or changes in light thereof will beapparent to persons skilled in the art. These are to be included withinthe spirit and purview of this application, and the scope of theappended claims, which follow.

1. A method for synchronizing a direct sequence spread spectrum (DSSS)frame, the method comprising: generating a preamble-codeword in afrequency domain for the DSSS frame by selecting a finite number ofnon-uniformly distributed frequencies corresponding to frequenciesdetectable by a Sparse Discrete Fourier Transform (SDFT) at whichspectral peaks will occur; generating a preamble in a time domain basedon the preamble-codeword; prepending the preamble to a coded data streamto form the DSSS frame; and transmitting the DSSS frame.
 2. The methodof claim 1, wherein each of the finite number of non-uniformlydistributed frequencies have higher spectral power than a backgroundpower spectral density of the preamble-codeword.
 3. The method of claim1, wherein the finite number of non-uniformly distributed frequenciescomprise randomly selected frequencies.
 4. The method of claim 1,wherein the finite number of non-uniformly distributed frequenciescomprise specifically selected frequencies.
 5. The method of claim 1,further comprising generating a different preamble-codeword after thepreamble-codeword has been used for a predetermined period of time. 6.The method of claim 1, further comprising: receiving the DSSS frame;generating sparse Fourier coefficients of the preamble-codeword byperforming the SDFT on the preamble; generating complex conjugates ofthe sparse Fourier coefficients based on a reference codeword; andmultiplying the sparse Fourier coefficients by the complex conjugates ofthe sparse Fourier coefficients.
 7. The method of claim 6, wherein thereference codeword comprises the preamble-codeword agreed upon inadvance between a transmitter and a receiver.
 8. The method of claim 6,further comprising generating a delay estimation signal by applying aniterative filtering algorithm to results of the multiplication.
 9. Themethod of claim 6, further comprising generating a delay estimationsignal by applying a Sparse inverse Discrete Fourier Transform (SiDFT)algorithm to results of the multiplication.
 10. A code acquisitionmodule for a direct sequence spread spectrum (DSSS) receiver, the codeacquisition module comprising: a Sparse Discrete Fourier transform(SDFT) module configured to perform an SDFT on a finite number ofnon-uniformly distributed frequencies comprising a preamble of areceived DSSS frame to calculate Fourier coefficients for the finitenumber of non-uniformly distributed frequencies; a multiplier configuredto multiply the Fourier coefficients for the finite number ofnon-uniformly distributed frequencies of the received DSSS frame bycomplex conjugate Fourier coefficients for the finite number ofnon-uniformly distributed frequencies to generate a cross-correlation ofthe received DSSS frame and the complex conjugate Fourier coefficients;and a filter module configured to input the cross-correlation and outputa delay estimation for the received DSSS frame.
 11. The code acquisitionmodule of claim 10, wherein the finite number of non-uniformlydistributed frequencies comprise sparsely allocated spectral peaksdetermined by a preamble-codeword.
 12. The code acquisition module ofclaim 10, wherein the complex conjugate Fourier coefficients arecalculated based on a reference codeword, wherein the reference codewordcomprises a preamble-codeword agreed upon in advance by the DSSSreceiver and a transmitter.
 13. The code acquisition module of claim 10,wherein the filter module is configured to accept an input signal fromthe multiplier, apply an iterative filtering algorithm to the inputsignal, and output a delay estimation signal.
 14. The code acquisitionmodule of claim 10, wherein the filter module is configured to accept aninput signal from the multiplier, apply a Sparse inverse DiscreteFourier Transform (SiDFT) algorithm to the input signal, and output adelay estimation signal.
 15. The code acquisition module of claim 10,wherein the SDFT module, the multiplier, and the filter module comprisea digital signal processor. 16.-20. (canceled)
 21. The method of claim1, wherein a ratio of preamble duration to coded data stream in eachDSSS frame is assigned to hide the spectral peaks of a preamble portionof the DSSS frame in a white noise spectrum of the coded data stream.22. The method of claim 1, further comprising generating a differentpreamble-codeword after the preamble-codeword has been used for apredetermined number of transmitted frames.
 23. The method of claim 3,wherein the randomly selected frequencies are randomly distributedwithin negative and positive frequencies.
 24. The method of claim 4,wherein the specifically selected frequencies are selected symmetricallyaround a center frequency.
 25. The code acquisition module of claim 10,wherein the SDFT module comprises an application specific integratedcircuit (ASIC).